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Meiliyani Siringoringo
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Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Mulawarman Jl. Barong Tongkok, Kampus Gunung Kelua Kota Samarinda, Provinsi Kalimantan Timur 75123
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INDONESIA
Eksponensial
Published by Universitas Mulawarman
ISSN : 20857829     EISSN : 27983455     DOI : https://doi.org/10.30872/
Core Subject : Economy, Science, Education,
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Mathematics Other
Jurnal Eksponensial is a scientific journal that publishes articles of statistics and its application. This journal This journal is intended for researchers and readers who are interested of statistics and its applications.
Arjuna Subject : Matematika - Statistik dan Probabilitas
Articles 205 Documents
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Analisis Faktor-Faktor Yang Berpengaruh Terhadap Pencemaran Air Sungai Mahakam Menggunakan Pemodelan Geographically Weighted Logistic Regression Pada Data Dissolved Oxygen Lestari, Vivi Dwi; Suyitno, Suyitno; Siringoringo, Meiliyani
EKSPONENSIAL Vol. 12 No. 1 (2021)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (694.948 KB) | DOI: 10.30872/eksponensial.v12i1.757

Abstract

Geographically Weighted Logistic Regression (GWLR) model is a local model of the logistic regression model applied to spatial data. Parameter estimation is performed at each observation location using spatial weighting. The spatial weighting is calculated by using an adaptive tricube function and bandwidth optimum was obtained based on Generalized Cross Validation (GCV) criteria. The purpose of this study was to obtain a GWLR model on the water pollution indicator Dissolve Oxygen (DO) in Mahakam River in East Kalimantan Province and to find factors affecting the probability of the Mahakam River water was not polluted based on DO indicator. The research data is secondary obtained from Environmental Department of East Kalimantan. The parameter estimation method was Maximum Likelihood Estimation (MLE). The research result showed that the closed form of ML estimator could not be found analytically and it can be approximed by using Newton-Raphson iterative methods. Based on the result of partial hypothesis test, the factors influencing the probability of the Mahakam River water was not polluted is different for every observation location. They were phosphate consentration, total dissolved solid and nitrite consentration. The factor influencing globally was total dissolved solid.
Deteksi Pencilan Spasial pada Data Kandungan Klorida di Sungai Mahakam Wilayah Samarinda Kalimantan Timur Muhammad Jainudin; Memi Nor Hayati; Ika Purnamasari
EKSPONENSIAL Vol 10 No 2 (2019): Jurnal Eksponensial
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (57.614 KB)

Abstract

Spatial data is data presented in the geographical position of an object, relating to the location in the space of the earth. In spatial data often have conditions that are not reasonable because the existence of outlier. Outlier referred to are spatial outlier that are defined as local instability or spatial objects that describe relatively extreme non-spatial attributes or differ significantly from other objects. The existence of outlier can have an impact on the results of model parameter estimates for example, which causes the estimation results to be biased. One method of outlier detection is spatial statistic Z test. This research aims to detect outlier chloride level data in seven locations on the Mahakam River of Samarinda area using spatial statistic Z test method. Based on the calculations with a significance level of 5% from the seven locations, there is one location which is outlier at the location IPA Tirta Kencana value equal to Zhit is 1.997.
Diagram Kontrol Short-Run untuk Memantau Variabilitas Proses Budi Nugroho; Desi Yuniarti; Sri Wahyuningsih
EKSPONENSIAL Vol 10 No 1 (2019)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (436.994 KB)

Abstract

Short run control chart is designed for production small scale and a limited amount data for monitoring different characteristic on same diagram control. The purpose of research is to know the implementation of short run control chart for monitoring mean and variability process based on characteristic data 1 inch Polyvinyl Chloride (PVC) in PT. Maspion. The objective of characteristics 1 inch pipe in this research are socket external diameter, socket internal diameter, barrel external diameter and barrel internal diameter. The Results showed that controlling process of by applying influence function, effective is to be applied to detect small movement in observation 11, 14, 14 and 9 for every control chart characteristic limited control 3σ.
Penggunaan Metode Kaizen Pada Tahap Improve Dalam Six Sigma Yuliana Yuliana; Yuki Novia Nasution; Wasono Wasono
EKSPONENSIAL Vol 8 No 1 (2017)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (177.109 KB)

Abstract

Six sigma is a holistic approach to solve the cause of disabilityproductsproblems and improve processes through the DMAIC (Define, Measure, Analyze, Improve, Control). Analyze the causes of product defect using the proposed improvement of Kaizen that is Five-M Checklist, 5W+1H (What, Why, Where, When, When, Who, How), and Five Step Plans. Obtained a better quality thereby creating customer satisfaction. The purpose of this study were to determine the value of Defect Per Million Opportunities (DPMO), Critical To Quality (CTQ) products, and know the process of production of bottled water brand RAMA volume 220ml. The result showed DPMO value 45.808. The level of the company be at 3,186 sigma with Critical To Quality (CTQ) is lid at 41,3%, water volume at 27,1%, and glass at 25%. The p-chart is used before and after improvement in this study to analyze the number of defective product. The result showed that before the repair using analysis of Kaizen, there is a lot of data out of the control limits, whereas after repair using analysis of Kaizen there is no data out of the control limits and some data products were near the centerline of the control p-chart.
Penerapan Metode Adams-Bashforth-Moulton pada Persamaan Logistik Dalam Memprediksi Pertumbuhan Penduduk di Provinsi Kalimantan Timur Apriani, Dewi; Wasono, Wasono; Huda, Moh. Nurul
EKSPONENSIAL Vol. 13 No. 2 (2022)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (716.25 KB) | DOI: 10.30872/eksponensial.v13i2.1046

Abstract

Logistic equation is a nonlinear ordinary differential equation that describes the population. Nonlinear ordinary differential equations can be solved by one of the numerical methods, namely the Adams-Bashforth-Moulton method. Adams-Bashforth-Moulton method is a multistep method which consists of Adams-Bashforth method as predictor and Adams-Moulton method as corrector. The logistic equation is solved first by using the Runge-Kutta method to obtain the four initial solutions, then followed by the Adams-bashforth-Moulton method. This study aims to predict population growth in the province of East Kalimantan using the Adams-Bashforth-Moulton method. Based on the calculation results obtained a numerical solution of the logistic equation for population growth at , with a step size of , the capacity of the province of East Kalimantan is and the growth rate of is 3,856,564 inhabitants.
Penerapan Metode If-Then dari Rough Set Theory dalam Menangani Kecelakaan Lalu Lintas di Kota Samarinda Tahun 2016 Martua Tri Januar Sinaga; Rito Goejantoro; Fidia Deny Tisna Amijaya
EKSPONENSIAL Vol 8 No 2 (2017)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (653.333 KB)

Abstract

Traffic accidents have caused many victims and lost materials, so itbecomes one of casesneed special attention every year. Therefore, it required a serious treatment to avoid the incidence of traffic accidents, so it can reduce the number of victimsbe inflicted. The aim ofthis study to determine the greatest factor/conditioncausing the fatality rate of traffic accidents and to determine the rules of decision rules from data that has been collected. The data used was secondary data taken from the report of traffic accidents recapitulation at Laka Lantas Unit, Satlantas Samarinda City. The analytical methods used to analyze the data are descriptive statistics analysis and Rough Set Theory. Based on the result, it can be seen the largest frequency of the victim who died is in traffic accidents that occur in sunny conditions. Moreover it is obtained 53 decision rules from the fatalities of victims by the traffic accidents in Samarinda City. The most powerful rule is "if a male student involved in a traffic accide nt at residential area and the road condition feasible passed by vehicles then the victim is likely to get serious injuries" with weight of 0.80.
Pengelompokan Kabupaten/Kota Di Pulau Kalimantan Berdasarkan Indikator Indeks Pembangunan Manusia Tahun 2020 Menggunakan Optimasi K-Means Cluster Dengan Principle Component Analysis (PCA) Anwar, Khoiril; Goejantoro, Rito; Prangga, Surya
EKSPONENSIAL Vol. 13 No. 2 (2022)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (964.676 KB) | DOI: 10.30872/eksponensial.v13i2.1053

Abstract

Data mining is a technique or process to obtain useful information from a large database. Based on its functionality, one of the tasks of data mining is to group data. Cluster analysis is an analysis that aims to group objects based on the information found in the data. One of the cluster analysis methods is the K-Means cluster method, which is a non-hierarchical grouping method by dividing the data set into a number of groups that do not overlap between one group and another. This study aims to classify districts/cities on the island of Kalimantan based on indicators of the human development index and obtain the sillhoutte coefficient value from the optimal cluster analysis using the K-Means algorithm on principle component analysis. The data used is the 2020 human development index data in districts / cities on the island of Kalimantan and used 8 variables from the human development index indicator. The results of the optimal cluster formed in the grouping of regencies/cities on the island of Kalimantan using the K-Means cluster method on the principle component analysis are 4 clusters. Cluster 1 has 20 regencies/cities, cluster 2 has 3 regencies/cities, cluster 3 has 26 regencies/cities and cluster 4 has 7 regencies/cities. The sillhoutte coefficient value for data validation from district/city clustering on the island of Kalimantan using the K-Means cluster method on principle component analysis produces 4 clusters of 0.540 which states that the cluster structure formed in this grouping is a medium structure.
Penentuan Percepatan Penyelesaian Proyek Pada Metode Jalur Kritis dengan Program Crash Wasono Wasono; Fidia Deny Tisna Amijaya; Moch Nurul Huda
EKSPONENSIAL Vol 10 No 1 (2019)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (322.598 KB)

Abstract

A project requires scheduling so that project completion time can be completed at the targeted time. Critical Path Method (CPM) is one of the scheduling methods that is able to provide solutions to scheduling problems. This method has several project acceleration methods to get the fastest turnaround time with a minimal increase in costs. The acceleration method is the program crashes by not using free float time. Case studies of project scheduling at the bus terminal administration office building in city X have been carried out. Analysis is carried out to obtain a critical path at normal times. At normal times, the implementation time is 385 days with a total cost of Rp. 488,488,000.00. After that the project was accelerated by using a crash program by not using the free float time and the implementation time being 289 days with a direct total project cost of Rp. 520,239,992.00. Based on the time of the acceleration of the crash by not using the free float time, the reduction time was 96 days with the addition of a total direct cost of Rp. 14.252.008.00
Prediksi Data Curah Hujan Dengan Menggunakan Statistika Non Parametrik Gracia Indah Fajarini; Ika Purnamasari; Sri Wahyuningsih
EKSPONENSIAL Vol 9 No 2 (2018)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (482.492 KB)

Abstract

Rainfall data analysis is the first stage of a water resource planning. One of rainfall data analysis method is using rain frequency analysis. In this research, rainfall frequency analysis is used to prediction the probability of occurrence from hydrological event. The maximum monthly rainfall frequency distribution is affects to rainfall during high repeat periods. Rainfall is the amount of water that falls on a flat surface during certain repetitive periods. Secondary data is got from Temindung Station of Samarinda City on 2007 to 2016. The type of distribution are used Normal, Gumbel, Log Pearson Type III, and Log Normal. Compatibility test of Non Parametric Statistics using Chi Square method. The results showed if the estimated rainfall at the highest repeating period of 2, 5, 10, 25, 50, and 100 years is Log Normal distribution. The distribution that requirement of qualify criteria is Log Normal and Gumbel distribution. The distribution that fit from Chi Square test is Gumbel distribution is 3,5177 and Log Normal distribution is 6,8945. From Kolmogorov Smirnov test the value of Gumbel distribution is 0, and Log Normal distribution is 0,0805. Rainfall patterns for Normal distribution, Gumbel distribution, Pearson Log distribution Type III and Log Normal distribution are horizontal patterns.
Analisis Cluster Non-Hirarki Dengan Menggunakan Metode K-Modes pada Mahasiswa Program Studi Statistika Angkatan 2015 FMIPA Universitas Mulawarman Nur Amah; Sri Wahyuningsih; Fidia Deny Tisna Amijaya
EKSPONENSIAL Vol 8 No 1 (2017)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (442.182 KB)

Abstract

Cluster analysis is a technique that used to categorize or classify object into clusters or group which is relatively homogeneous. This research aims to know the number of the best cluster used in the selection of Statistics major using K-Modes Cluster, which variable as the best center of cluster & the most optimum, and also comparison of the cluster based on the Davies-Bouldin Index (DBI) which is derived in each cluster are 2 clusters, 3 clusters, and 4 clusters. Steps in this research is descriptive analysis, validity and reliability of questionnaire, determine the number of clusters, compute the dissimiliarity distance, calculate the cluster validation and interpretate the result of the best cluster. Selection of the best cluster use the smallest value comparison. The smallest of the two clusters are 0,599. The center (centroid) of clusters variables which is the best optimum using K-Modes with two clusters are for the first centroid is the first choice of major, SNMPTN, IPK satisfactory, study routines for 4 times a week, and the average length of study is between 60 minutes to 120 minutes per day.; for the second centroid is the first choice of study program, SNMPTN, IPK is very satisfied, study routines for 6 times a week, and the average length of study is less than or equal to 60 minutes per day. The final results showed that the best cluster produced is two clusters where cluster 1 consisted of 37 students and cluster 2 consisted of 8 students.

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